Simultaneous quantification of selective serotonin reuptake inhibitors and metabolites in human plasma by liquid chromatography-electrospray mass spectrometry for therapeutic drug monitoring.

A simple and sensitive liquid chromatography-electrospray ionization mass spectrometry method was developed for the simultaneous quantification in human plasma of all selective serotonin reuptake inhibitors (citalopram, fluoxetine, fluvoxamine, paroxetine and sertraline) and their main active metabolites (desmethyl-citalopram and norfluoxetine). A stable isotope-labeled internal standard was used for each analyte to compensate for the global method variability, including extraction and ionization variations. After sample (250μl) pre-treatment with acetonitrile (500μl) to precipitate proteins, a fast solid-phase extraction procedure was performed using mixed mode Oasis MCX 96-well plate. Chromatographic separation was achieved in less than 9.0min on a XBridge C18 column (2.1×100mm; 3.5μm) using a gradient of ammonium acetate (pH 8.1; 50mM) and acetonitrile as mobile phase at a flow rate of 0.3ml/min. The method was fully validated according to Société Française des Sciences et Techniques Pharmaceutiques protocols and the latest Food and Drug Administration guidelines. Six point calibration curves were used to cover a large concentration range of 1-500ng/ml for citalopram, desmethyl-citalopram, paroxetine and sertraline, 1-1000ng/ml for fluoxetine and fluvoxamine, and 2-1000ng/ml for norfluoxetine. Good quantitative performances were achieved in terms of trueness (84.2-109.6%), repeatability (0.9-14.6%) and intermediate precision (1.8-18.0%) in the entire assay range including the lower limit of quantification. Internal standard-normalized matrix effects were lower than 13%. The accuracy profiles (total error) were mainly included in the acceptance limits of ±30% for biological samples. The method was successfully applied for routine therapeutic drug monitoring of more than 1600 patient plasma samples over 9 months. The β-expectation tolerance intervals determined during the validation phase were coherent with the results of quality control samples analyzed during routine use. This method is therefore precise and suitable both for therapeutic drug monitoring and pharmacokinetic studies in most clinical laboratories.

The impact of triathlon training and racing on athletes' general health.

Although the sport of triathlon provides an opportunity to research the effect of multi-disciplinary exercise on health across the lifespan, much remains to be done. The literature has failed to consistently or adequately report subject age group, sex, ability level, and/or event-distance specialization. The demands of training and racing are relatively unquantified. Multiple definitions and reporting methods for injury and illness have been implemented. In general, risk factors for maladaptation have not been well-described. The data thus far collected indicate that the sport of triathlon is relatively safe for the well-prepared, well-supplied athlete. Most injuries 'causing cessation or reduction of training or seeking of medical aid' are not serious. However, as the extent to which they recur may be high and is undocumented, injury outcome is unclear. The sudden death rate for competition is 1.5 (0.9-2.5) [mostly swim-related] occurrences for every 100,000 participations. The sudden death rate is unknown for training, although stroke risk may be increased, in the long-term, in genetically susceptible athletes. During heavy training and up to 5 days post-competition, host protection against pathogens may also be compromised. The incidence of illness seems low, but its outcome is unclear. More prospective investigation of the immunological, oxidative stress-related and cardiovascular effects of triathlon training and competition is warranted. Training diaries may prove to be a promising method of monitoring negative adaptation and its potential risk factors. More longitudinal, medical-tent-based studies of the aetiology and treatment demands of race-related injury and illness are needed.

Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data.

Microstructure imaging from diffusion magnetic resonance (MR) data represents an invaluable tool to study non-invasively the morphology of tissues and to provide a biological insight into their microstructural organization. In recent years, a variety of biophysical models have been proposed to associate particular patterns observed in the measured signal with specific microstructural properties of the neuronal tissue, such as axon diameter and fiber density. Despite very appealing results showing that the estimated microstructure indices agree very well with histological examinations, existing techniques require computationally very expensive non-linear procedures to fit the models to the data which, in practice, demand the use of powerful computer clusters for large-scale applications. In this work, we present a general framework for Accelerated Microstructure Imaging via Convex Optimization (AMICO) and show how to re-formulate this class of techniques as convenient linear systems which, then, can be efficiently solved using very fast algorithms. We demonstrate this linearization of the fitting problem for two specific models, i.e. ActiveAx and NODDI, providing a very attractive alternative for parameter estimation in those techniques; however, the AMICO framework is general and flexible enough to work also for the wider space of microstructure imaging methods. Results demonstrate that AMICO represents an effective means to accelerate the fit of existing techniques drastically (up to four orders of magnitude faster) while preserving accuracy and precision in the estimated model parameters (correlation above 0.9). We believe that the availability of such ultrafast algorithms will help to accelerate the spread of microstructure imaging to larger cohorts of patients and to study a wider spectrum of neurological disorders.

Assessment of bioaerosols and inhalable dust exposure in Swiss sawmills

An assessment of wood workers' exposure to airborne cultivable bacteria, fungi, inhalable endotoxins and inhalable organic dust was performed at 12 sawmills that process mainly coniferous wood species. In each plant, samples were collected at four or five different work sites (debarking, sawing, sorting, planing and sawing cockpit) and the efficiency of sampling devices (impinger or filter) for determining endotoxins levels was evaluated. Results show that fungi are present in very high concentrations (up to 35 000 CFU m(-3)) in all sawmills. We also find that there are more bioaerosols at the sorting work site (mean +/- SD: 7723 +/- 9919 CFU m(-3) for total bacteria, 614 +/- 902 CFU m(-3) for Gram-negative, 19 438 +/- 14 246 CFU m(-3) for fungi, 7.0 +/- 9.0 EU m(-3) for endotoxin and 2.9 +/- 4.8 g m(-3) for dust) than at the sawing station (mean +/- SD: 1938 +/- 2478 CFU m(-3) for total bacteria, 141 +/- 206 CFU m(-3) for Gram-negative, 12 207 +/- 10 008 CFU m(-3) for fungi, 2.1 +/- 1.9 EU m(-3) for endotoxin and 0.75 +/- 0.49 mg m(-3) for dust). At the same time, the species composition and concentration of airborne Gram-negative bacteria were studied. Penicillinium sp. were the predominant fungi, while Bacillus sp. and the Pseudomonadacea family were the predominant Gram-positive and Gram-negative bacteria encountered, respectively. [Authors]

Sensoriamento remoto na determinação de atributos de um nitossolo sob aplicação de vinhaça

O sensoriamento remoto vem sendo utilizado na avaliação de características químicas e físicas dos solos, como fonte de informação rápida, não destrutiva e de baixo custo, podendo assim auxiliar no gerenciamento de passivos ambientais. Nesse sentido, este trabalho teve por objetivo verificar o potencial da utilização de dados hiperespectrais na determinação de algumas propriedades de um solo submetido a diferentes aplicações de doses de vinhaça, utilizando dados espectrais oriundos de amostras em condições de campo e de terra fina seca em estufa. O experimento, delineado em blocos ao acaso constou de seis tratamentos e quatro repetições, sendo os tratamentos: 1, sem vinhaça; 2, fertirrigado com químicos; e 3, 4, 5 e 6, com aplicação de, respectivamente, 150, 300, 600 e 900 m³ ha-1 de vinhaça. Foram gerados modelos para predição de alguns atributos químicos e físicos do solo para os dois tipos de amostras, a partir de curvas espectrais na região do visível e infravermelho próximo. Para determinação da granulometria, os modelos não foram influenciados pelo tipo de amostra utilizada e foram classificados como "aceitáveis" a "bons" (R² entre 0,7 e 0,9). Em relação aos atributos químicos, foram gerados modelos com capacidade de diferenciação apenas entre altas e baixas concentrações (R² entre 0,50 e 0,65) para os atributos pH, matéria orgânica, H+Al e capacidade de troca catiônica, sendo os gerados para terra fina seca em estufa em alguns casos melhores que os para amostras em condições de campo.